Mid-Level Data Scientist

Summary

Join EcoVadis's AI Center of Excellence as a Mid-Level Data Scientist and contribute to building a sustainable future. You will work with a team of 25 scientists and engineers, leveraging machine learning and NLP to solve complex business problems. Responsibilities include working with large datasets, building and maintaining ML models, and collaborating with customers. A Master's degree in a quantitative discipline and 2+ years of experience in machine learning/NLP are required. The position offers flexible working hours, wellness allowances, professional development opportunities, and a hybrid work organization, with options for remote work from Spain or abroad.

Requirements

• Master’s degree in quantitative discipline (e.g., Statistics/Applied Math, Data Science, Artificial Intelligence, Computer Science or a related field)
• 2+ years of overall experience in Machine Learning/NLP and data mining techniques
• Knowledge of Machine Learning algorithms, frameworks and libraries, including deep learning frameworks
• Good understanding of text representation techniques and experience in implementing NLP solutions (e.g., named entity recognition, information retrieval, question answering)
• Strong analytical, mathematical, and coding skills
• Strong communication skills

Responsibilities

• Work with large, complex data sets to solve challenging business problems by applying advanced analytical methods as needed
• Articulate and translate business questions into technical solutions
• Build, benchmark, and maintain machine learning models and identify data annotation efforts
• Leverage Python, MLflow, Azure stack (e.g., Azure cloud, Azure ML, Azure Data Factory) and Databricks to deliver end-to-end solutions
• Stay in close contact with customers to evaluate their needs and recommend solutions that increase customer satisfaction and drive business value

Preferred Qualifications

Any experience with Azure or other cloud provider

Benefits

• Support with all the necessary office and IT equipment
• Flexible working hours
• Wellness allowance for mental and physical wellbeing
• Access to professional mental health support
• Referral bonus policy
• Learning and development
• Sustainability events and community involvement
• Peer recognition program
• Employee-led resource groups
• Hybrid work organization (from the office or from home)
• Remote work from abroad policy
• Meals and Transportation Vouchers (Cobee card)
• Dental Benefits
• Life & Accident Insurance + Private Health Insurance
• Paid employee volunteer day
• Paid moving day (1/year)
• Time off: 1 Community Service Day + 1 Personal Day
• Summer Hours in July and August (36 hours per week)
• Hybrid Monthly Allowance for electricity and Internet